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"What gets measured, gets managed". —Peter Drucker

I’ve been in human resources and talent acquisition for 20 years and one of the core bedrocks of my approach in every role has been to clearly understand the metrics that underpin what I’m trying to achieve. 

Developing a solid grounding with your HR metrics gives you the essential base to build on more sophisticated analysis as you develop your capabilities.

Here, I’ll set out a few guiding principles that will make your journey more efficient and provide best practices for ensuring the reliability and credibility of your data.

This is aimed at small/mid-sized businesses that haven't yet matured their people metrics capability or as a refresher for more established setups. 

We’ll cover:

What are HR Metrics?

For me, the best description of HR metrics is that they are discrete measurements of people activity that can be used to indicate performance against organisational objectives.

In other words, HR metrics are the facts of your organisation—they aren't opinions, they aren't estimates, they're the facts about the people in your organisation.

Alone they don’t tell a story but, once you combine them with richer information and other business data and metrics, you can build an accurate picture of what drives success.

Why do we need HR metrics?

In every business people are crucial. They’re normally the biggest cost and a critical success factor in the continued success of every business.

As such, as we measure our business growth in terms of the number of customers, revenue, profit, and value, it makes perfect sense to measure the people elements at the same time. 

It seems obvious, but we need to know how many people work at our organisations (and a lot about them too). But, as many of you will know already, getting that number accurate every time takes a degree of work.

So, by setting out a number of measurements that you feel represent your organisation effectively, you’re able to give an accurate picture of it.

By doing this you take control of the conversation internally and, by sharing this information in a way that invites feedback, you'll also learn what else the organisation wants to know about.

So, going back to our definition of an HR metric (each one is a fact that there can only be one correct answer at a given time) the most important lesson I learned is that you need to be clear on the calculation method. 

This sounds straightforward but it comes with headaches…

A quick aside

I'll now divert into a quick story about how I ended up first becoming interested in this field.

I once joined a company to set up and grow the talent acquisition function. For the first six months, I gathered as much data as I could on our hiring practices: source/cost/time/location/function/role type—all of the typical hiring data you might expect. 

I put this in various presentations to make the case for the changes I felt were necessary. Then, one day, we had a problem. 

On an investor call, someone asked a question about our headcount because the numbers didn't look right. Guess what, they were right and we were wrong!

The problem landed on my desk, I can't really remember why but probably because I'd tried to use data to drive action. But what I do remember is sitting in a very hot meeting room for what felt like a week (but was probably only a couple of days) tracing through what data was sent to our finance team, its origin, and its accuracy to try and find out how it could be incorrect in our public statements.

It came down to 2 very simple problems:

1) We sent them data from our HR system (our very old, very rubbish HR system) on a set date and it transpired that people updated the old, rubbish HR system with new starters and leavers in time for payroll and not in time for this report. So the data was never correct, it couldn't be.

2) We sent them an aggregated headcount that included contractors (as that was the report that had always been sent) and nobody, as far as I could tell, ever questioned or asked what the numbers meant.

There were a number of other headaches as well but these were the two key points. This led to us refreshing our on and offboarding processes, redoing how we calculated the headcount that we shared, and unifying those processes.

I know this seems very basic but it’s a good example of how easy it is for these things to go awry.

So, story over and we can draw out some…

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Principles for your HR Metrics

1) Be clear about what the metric is.

2) Be clear about how it is calculated and what your data sources are.

3) Be clear that you understand and can audit the processes that feed into the metric.

Once you have a stable set of metrics, you then have the opportunity to combine and interpret them to create a picture of what’s happening in your organisation and what you might want to do to change them. 

For example, if ‘time to hire’ and 'recruiter’s average number of job requisitions' are climbing, are more recruiters a potential solution?

40 key human resources metrics you should Track and how to assess them

40 key human resources metrics you should look at and how to assess them graphic


This is the most obvious one. Aim to show the number of employees you have (permanent and contractors if that’s relevant for your business), where they are based, in which office, and in which executive department they sit.

Attrition and retention rate

  • Turnover rate. How many people are leaving and from which location/executive department/demographic?
  • Why are they leaving—voluntary/non-voluntary? 
  • Average tenure of leavers 
  • What is your attrition rate? (and your calculation needs to be consistent here). My suggestion for attrition is: 

Number of leavers over last 12 months/((permanent headcount 12 months ago + permanent headcount today)/2)

Many people prefer to have attrition measuring just voluntary leavers, both measures are needed and you can choose what is the headline method.

  • What is your retention rate? Normally calculated annually.:

    Number of individual employees who remained employed for entire measurement period / number of employees at start of measurement period x 100

Recruitment metrics

  • How many people are you hiring and in what location/executive department?  
  • How long is it taking you to hire someone for specific roles? 
  • What sources of hire are most successful? 
  • How costly is hiring? Could be the average cost per hire
  • Vacancies per recruiter
  • Number of applications 
  • Number of interviews
  • Job offer acceptance rate (%)  
  • LinkedIn (other social?) followers 
  • Glassdoor rating.

Demographics - Who are your people? 

  • Gender split
  • Nationality
  • Tenure
  • Other diversity measures such as age, education level, or ethnicity. Can further split this by location/executive department depending on what you have today and what’s important to your organisation.

Organisational measures

  • Percentage of managers
  • Span of control
  • Number of people at each layer in the business
  • Number of open vacancies
  • Growth over time.


  • How many holidays used and remaining by individuals and by the business
  • Sicknesses
  • Work from home/abroad arrangements 
  • Taken/left from holiday allowance.


  • Hours of learning
  • Number of mentorships
  • Mandatory training completion
  • Type of learning (online vs classroom)
  • Training budget spent.

Performance metrics

  • Percentage of employees with goals
  • Performance/potential/loss impact rating by location/executive function.


  • Total payroll expenditure
  • Payroll expenditure as % of revenue
  • Gender pay gap
  • Benefit participation rates.


  • Employee engagement score by location and executive department. This depends on what tools (if any) you have in place for engagement and the score is dependent on that methodology. 

    There are a number of different engagement metrics you can use e.g intent to stay or net promoter score.

These may not be the perfect set of metrics for your organisation but they’re a starting point to get you thinking about what’s right.

Whilst some of these have very obvious calculation methods others are open to interpretation and that’s fine. The main thing to be wary of is being consistent and being clear when you’re communicating how something's calculated and therefore what it means.

How to collect HR Metrics

All of the data that you have is likely to sit in different places e.g. your HRIS/HRMS, learning management system, employee engagement software, applicant tracking system, time tracking software, or maybe even spreadsheets.

As stated above, for each of your metrics you need to be clear about what it is, what the data source is, how it's calculated, and how we would audit the underlying process that supports it.

So if we take 'number of leavers in a month' this could be:

  • What is it? Permanent employees leaving location/function/company/team in a given calendar month.
  • Data source. HRIS report: leavers by month.
  • How it’s calculated. Permanent employees leaving from the 1st to the last day of month (garden leave calculated as last day of employment). Any leavers who are missed we recalculate for previous months and make a note in the metrics pack.
  • Underlying processes. Check payroll is aligned with leavers, any leaver checklists you might have, and redundancy lists. Revisit any mistakes from previous months with clear trails back to the source so you can see what went wrong.

By ensuring you have this level of rigour with each metric you will build strong, stable underlying data and processes that support the development of a more mature analytics capability in the future, as well as solid processes that underpin the whole HR team.

Presenting HR metrics

The next challenge you have is how to share this information.

Visualising your data is critical because as you gather this data and share it over time it tells a story. Are you growing as an organisation, are you growing quickly enough? Is your gender pay gap widening?

These are all comparable measures that are only possible by collating and reporting on this data regularly.

In terms of how to best visualise the data, here are some pointers.

  • Use graphs rather than a table of numbers where possible, Excel is a great tool here
  • Set it up so you can see progress over time (monthly or quarterly)
  • Use your company colour scheme and presentation layout
  • Add simple commentary to the presentation to explain anything that isn’t clear or to contextualise change.

Wrapping up 

To summarize:

  • Agree on your metrics based on what makes sense for your organization
  • Be clear on calculation and make sure it's auditable and consistent
  • Display them clearly
  • Repeat consistently.

If you do this, you’ll build credibility in using HR data and set your business up for more detailed analysis. Complex HR data analysis can only be done on good data—following these steps will set you up perfectly for that.

Further resources to help you build a well-oiled HR function:

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By Liam Reese

Liam has worked developing HR Teams in Tech businesses to be scalable for the last 15 years. He is passionate about the impact people have on a business and the role HR plays in that.